Paper 1 : Predicting Depression via Social Media<\/p>\n
Paper 2 : Understanding Anti-Vaccination Attitudes in Social Media<\/p>\n
<\/p>\n
The two papers are more distinct than the previous papers for reflections, even though they deal with the issues within the same sphere.<\/p>\n
Paper 1 takes a very important topic which is very relevant to everyone, predicting traits of depression through social posts.
\nThe authors observe depression through tweets of the user. A user who is not much active\/expressive on twitter cannot be of much help in predicting depression. On the other hand, active twitter users show a lot of sign of going into depression as well as on using anti-depressants. The authors observerd that the traits included negative langauge in tweets and lesser interactions with replies and DM. Are these results generizable to other social platforms ? Can a youtuber ‘s depression predicted by the facial experssions and language on his\/her videos ?\u00a0 On extending it youtube, more parameters need to be taken into consideration.<\/p>\n
Paper 2 analyses the behavior of anti-vaccinners. It observes how earlier concept of herd community to vaccination is failing due to online information sharing. The authors focus on three groups – pro-vaccine, anti-vaccine and those who recently switch to anti-vaccine and what triggers that. One interesting note in the paper is that they don’t take into account the people who switch to pro-vaccine and their triggers. I believe it will shed some light over what makes someone realise that they were part of a conspirationalist group. This can be used to create methods which reverse the effects of brainwashing by such anti-vaccine groups.<\/p>\n
The paper uses MEM topic model to categories user tweets into themes of the tweets anti-vacciners tweet and care about. It doesn’t take into the account of virality of the news topic. For example, during the Syrian revolution, a lot of people were tweeting about government, war, violence etc. The authors don’t mention that if they have taken care to minimize effects of viral news of the tweet topics. <\/p>\n","protected":false},"excerpt":{"rendered":" Paper 1 : Predicting Depression via Social Media Paper 2 : Understanding Anti-Vaccination Attitudes in Social Media The two papers are more distinct than the previous papers for reflections, even though they deal with the issues within the same sphere. Paper 1 takes a very important topic which is very relevant to everyone, predicting […]<\/p>\n","protected":false},"author":138,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-401","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/posts\/401","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/users\/138"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/comments?post=401"}],"version-history":[{"count":2,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/posts\/401\/revisions"}],"predecessor-version":[{"id":405,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/posts\/401\/revisions\/405"}],"wp:attachment":[{"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/media?parent=401"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/categories?post=401"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/cs6724spring18\/wp-json\/wp\/v2\/tags?post=401"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nThe anti-vacciners group show a close-knit group characteristics. This is equally true in real life also. People generally stay with other people with similar viewpoints or at least compatible <\/strong>view points.<\/strong> This brings to the paper’s conclusion which states that small triggers are enough for a person to join the anti-vaccine group. In my opinion, those people have a long exposure to such thinking outside of twitter and they get vocal only when they join a certain group.<\/strong><\/p>\n